Editorial Recent Advances in RF Propagation Modeling for ...downloads.hindawi.com/journals/ijap/2017/4701208.pdf · InternationalJournalofAntennasandPropagation 3 that is, the Wireless

EditorialRecent Advances in RF Propagation Modeling for 5G Systems

Mihajlo Stefanovic,1 Stefan R. Panic,2 Rausley A. A. de Souza,3 and Juan Reig4

1Faculty of Electrical Engineering, University of Nis, Nis, Serbia2Faculty of Natural Science and Mathematics, University of Pristina, Kosovska Mitrovica, Serbia3National Institute of Telecommunications (Inatel), Santa Rita do Sapucaı, MG, Brazil4Institute of Telecommunications and Multimedia Applications (iTEAM), Universitat Politecnica de Valencia, Valencia, Spain

Correspondence should be addressed to Stefan R. Panic; [email protected]

Received 30 July 2017; Accepted 30 July 2017; Published 15 October 2017

Copyright © 2017 Mihajlo Stefanovic et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

Continuously increasing demand for higher data rates,larger network capacity, higher energy efficiency, and highermobility has motivated research within fifth-generation (5G)communication systems modeling. 5G is generally agreedfor a set of new requirements for wireless communicationssystems. These requirements will need to address severalcritical performance areas including cost constraints, traf-fic latency, reliability, security, availability, heterogeneousstructure of networks, multicast/broadcast requirements, therequirement to serve a variety of different devices, andreduced energy consumption. Accurate 5G indoor and out-door channel characterization and modeling are crucial fordetermining the system performance and thus for systemand for 5G network realization. Namely, 5G radio frequency(RF) propagation is affected by various phenomena thatmoreor less deteriorate the original transmitted signal arrivingat the receiver (free-space propagation, object penetration,reflection, scattering, diffraction, and absorption caused byatmospheric gases, fog, and precipitation).

To generate reliable propagation models for 5G systemsand further to determine standard performance measure-ments of 5G systems, corresponding path loss models mustbe built for link budget evaluation and signal strength pre-diction, with the inclusion of directional and beamformingantenna arrays and cochannel interference, while temporaldispersion caused by multipath propagation (impacting thetiming, packet and frame sizes, and other air interface designparameters) should also be characterized. Therefore, generalstatistical models could not be sufficient in order to assess

the performance of system and specific models related toreal-world reference scenarioswith fine classification of termswill be required.

For the development of new 5G systems to operate inmillimeter bands, there is a need for accurate propagationmodeling at these bands. Exploitation of unused millimeterwave (mmWave) band spectrum (spectrum between 6 and300GHz) is an efficient solution for meeting the standardsfor 5G networks enormous data demand growth explosion.Measurements provided at 38GHz (Base Station-to-MobileAccess Scenario [1] and Peer-to-Peer Scenario [2]), 60GHz(Peer-to-Peer Scenario and Vehicular Scenario [3]), and73GHz [4] have clearly identified the existence of non-line-of-sight (NLOS) conditions. One of the most inten-sively used statistical models for characterizing the complexbehavior and random nature of NLOS fading envelope isthe Nakagami-m distribution. In [5–7] for the purposeof modeling observed 5G system propagation properties,the Nakagami-m parameter is directly computed from themeasured data. Two most well-known procedures used forthe estimation of the Nakagami-m fading parameter, m, are(1) maximum likelihood (ML) estimation and (2) moment-based estimation. However, it is known that sample momentsare often subjected to the effects of outliers (even a smallportion of extreme values, outliers, can affect the Gaussianparameters, especially the higher order moments). Moreover,occurrence of outliers is especially problematic when higherorder sample moments are used for estimation, since esti-mation inaccuracy arises in such cases. Providing the best

HindawiInternational Journal of Antennas and PropagationVolume 2017, Article ID 4701208, 5 pageshttps://doi.org/10.1155/2017/4701208

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2 International Journal of Antennas and Propagation

moment-based estimator is still major issue that should beaddressed.

Because of that, there is a need for developing a novelapproach for NLOS channels parameter estimation based onperformance measurements, which will enable us to estimatepropagation parameters in real time and to avoid weaknessesof ML and moment-method estimation approaches.

Stochastic channel models for mmWave communicationsin both indoor and outdoor environments have been mostlycharacterized with a Rician distribution in line-of-sight(LOS) environments where a dominant path is present [8].In [8] it has been shown that Ricean K-factor is rangingover a defined set of values for observed LOS and NLOSconditions in vertical-to-vertical (V-V) copolarized antennascenario and corresponding set of values for observed LOSand NLOS conditions vertical-to-horizontal (V-H) cross-polarized antenna scenario. However, despite the fact shownin [8] that Rician distribution provides the best fit to themeasurement data, results of [8] imply that conventionalfading models fall short of accurate modeling of the randomfluctuations of 5G wireless channel signal. In [9] it has beenconcluded that for accurate 5G systems channel modeling,proposed models should ensure that the channel LOS andNLOS conditions, the second-order statistics of the channel,and the channel realizations should change smoothly in thefunction of time, antenna position, and/or frequency. There-fore a need arises for novel characterization of propagation inLOS conditions, by observing Ricean K-factor as a randomprocess.

In particular, the diversity of scenarios envisaged for the5G applications at the mmWave band will certainly lead toa variety of propagation conditions. Currently, an enormousvariety of waveforms are considered to be potential candi-dates for the 5G air interface. They include (i) single-carrierfrequency divisionmultiplexing (SC-FDMA), already used in4G Long-Term Evolution (LTE) uplink, also called differentlygeneralized discrete Fourier transforms- (GDFTs-) orthogo-nal frequency division multiplexing (OFDM) [10]; (ii) zero-tail (ZT) or unique-word (UW) DFT-spread-OFDM [11,12], ultra-wideband- (UW-) OFDM, generalized frequencydivision multiplexing (GFDM) [13], and cyclic prefix- (CP-)OFDM(already used in the 4GLTE downlink); (iii) resource-block-filtered OFDM, filter-bank-multicarrier (FBMC), anduniversal filter multicarrier (UFMC). As it can be seen,the OFDM technique is omnipresent in the 5G waveformproposals.TheOFDM technique shall certainly remain as theroot framework for the new 5G waveform design, with someoptimization to support the new 5G requirements [14, 15].

Therefore it is necessary to propose an efficient, simple,and general method to generate samples for general 5Gchannel and further to make use of this channel in order toassess the bit error rate performance of an OFDM systemmodel.

Stochastic geometry has been a powerful technique toevaluate system performance in conventional cellular net-works [16], which reveals the impacts of multiple systemparameters such as base station density, transmit power, andpath loss exponent on the performance parameters such asdata rate or reliability. The key idea in [17] is to model

random obstacles (e.g., buildings) as rectangles with randomsizes and orientations whose centers form a Poisson pointprocess (PPP) in 2-dimensional space. However, instead ofone-hop communication between the macro cell base station(MBS) and a single small cell base station (SBS) cluster, the5G cellular networks may have multiple SBS clusters, whichrequire multihop transmissions to improve the cell coverage.Considering the distance-dependence of the blockage effects(i.e., the likelihood of a blockage event increases as thedistance increases) at mmWave, multihop communicationcan be an effective solution to build mmWave wirelessbackhaul systems. In this context, motivated by the limitationin [18], the single-hop wireless backhaul system from [18] canbe extended to a multihop scenario with multiple SBS clus-ters. Multiple points-to-multiple-points (MBMs-to-MBMs)links could be also studied, instead of [18] single-point-to-multiple-points (MBS-to-SBSs) links. Therefore, with dif-ferent distance statistics from [18], the intercluster SBS-to-SBS communication can benefit from higher order of spatialdiversity compared to the MBS-to-SBS communication in[18].

From this point of view, the analysis of an optimal andsuboptimal hop count to minimize the end-to-end outageperformance between the MBS and the destination SBScluster for a given end-to-end distance could be of interest,where the suboptimal hop count is based on only the per-hopoutage performance.

Interference issues will become of crucial importance dueto the coexistence of 5G devices, since a number of mmWavedevices are expected to grow extensively in the near future[19]. In order to satisfy 5G quality-of-standard requirementsand meet user mobility, due to the higher path loss atmmWave frequency range, multiple antenna arrays could beused in outdoormmWave systems for providing an additionalgain [20, 21]. The increasing growth of 5G devices numberwill prompt the study of array pattern nulling techniques.The objectives of design of the antenna arrays are to achievea minimum side lobe level (SLL) and a narrow first nullbeam width (FNBW). Methods used for the antenna arraysynthesis can be classified into two categories: deterministicand stochastic. The biggest advantages of using stochasticmethods are their ability in dealing with large number ofoptimization parameters and avoiding getting stuck in localminimum.

An interesting idea for 5G mmWave antenna array syn-thesis could be based on genetic algorithm for the synthesis oflinear array with nonuniform interelement spacing in orderto obtain the optimal position of the elements in order toobtain the minimum side lobe level and nulls in desireddirections.

The use of mmWave bands for next-generation wirelesssystems could offer ultra-wideband spectrum availability andincreased channel capacity. All these benefits come at theexpense of potentially higher system complexity particularlyin terms of radio frequency (RF) front end and antennadesign. However, the recent advancements around mmWavewireless systems development have produced cost-effectivesolutions that can be leveraged to overcome these challenges.60GHz frequency band has its own standardized protocol,

International Journal of Antennas and Propagation 3

that is, the Wireless Gigabit Alliance (WiGig) standardwhich is equivalent to IEEE 802.11ad [22]. A promisingstudy would be the link budget estimation, performed basedon WiGig/IEEE 802.11ad standard-defined modulation andcoding scheme (MCS) modes and 60GHz mmWave specificpath loss and auxiliary attenuation factors. The consideredsystems parameters for this link budget estimation couldbe obtained from real-world hardware prototypes for next-generation mmWave mesh backhaul networks in industry.

Although multiple-input and multiple-output (MIMO)techniques have been widely employed in cellular andwireless local area network systems working at sub-6GHz[23–25], the potential realizations of MIMO technique inmmWave band are not fully understood yet, consideringthe unique multipath propagation characteristics and theincreased path loss over the lower frequency bands used incurrent 3G/4Gwireless communication. Spatial multiplexing(SM) and beamforming (BF) are the two most commonlyused approaches to realize aMIMO system.Themultiplexinggain can be obtained by exploiting the spatial difference ofthe channel response in different transmit- (Tx-) receive (Rx)element pair. On the other hand, in the mmWave band, thepropagation loss is higher compared to the lower frequencies;thus the high-gain antenna arrays are expected to compensatethe increased path loss. Several researches have conductedanalyses on the performance of SM and BF in the mmWavecommunications. The feasibility of indoor mmWave MIMOhas been investigated by ray-tracing based channelmodeling,by virtual antenna array based channelmeasurement [26, 27],and also by a 2 × 2 microstrip array in an underground mineenvironment [28].The performance of a hybrid transmissioncombining BF and SM in mmWave communication is alsoanalyzed based on a ray-tracing method in both LOS andmultipath environment [29].

It could be of interest to provide the measurement-based channel capacity comparison between SM and BFunder realistic antenna arrays, with the same Tx power, thesame array position, and the same propagation condition.In particular, a SM system could be analyzed and dividedinto 4 subarrays, each one of them consisting of 4 elements,corresponding to a 4 × 4 MIMO system, while in the BFsystem, the antenna array could be constructed by the whole16 elements, which corresponds to a single-input and single-output (SISO) system but with a larger array gain than that ofthe SM system.

The introduction ofMIMOand receiver diversity wirelessdevices provides large gains in the throughput performance.These gains are highly dependent on the performance of thereceiving-antenna system and the receiving algorithm [30].The devices can change the behavior of the antenna systems,for example, by using beamforming mechanisms, and alsocan adapt software algorithms to suit the environment theyare currently used in. Wireless equipment manufacturersas well as network providers are pushing to have perfor-mance tests of the hand-held devices. Network providersexpect to recommend the user equipment (UE) with thebest performance to their customers; manufacturers wishto be able to compare the quality of their own UE to theone of the competitors. These comparisons should include

the effect of the antenna systems, the analog frontends,digital receiving algorithms, and baseband processing. Oneof the methods proposed by 3GPP, yet very promising one,is the decomposition method (DM). Over-the-air (OTA)throughput tests of wireless MIMO devices are an importanttool for network operators and manufacturers. The UE isplaced in an anechoic chamber and a random fading processis emulated by a base station emulator (BSE). The antennacharacteristic of the UE is taken into account by sampling thesphere around the UE with the BSE test antenna at a largenumber of positions. For low-variance throughput results,long measurement intervals over many fading realizationsare required, leading to long and expensive measurementperiods in an anechoic chamber. Analyzing the possibilities ofspeeding upOTA testing throughupgradingmethods forDManalysis could be interesting task in performing throughputtesting of wireless MIMO devices.

Attenuation by a human body and trees and penetrationlosses of material at the ITU proposed frequency bands [31],24.25–27.5 and 37–40.5GHz, are important issues for future5Gwireless access systems. In [31] the attenuation by a humanbody and trees and penetration loss of differentmaterials with1 GHz bandwidthweremeasuredwith a time domain channelsounder at 26 and 39GHz, respectively. As far as we know,there are no measurements and modeling work reportedin open literature on human blockage, attenuation by trees,and penetration loss of different materials at 24.25–27.5 and37–40.5GHz frequency bands. The prediction of attenuationby a human body and trees and the penetration losses inthis work are important and necessary for future mmWavewireless communication systems deployment. By consideringa human body as an infinite absorbing screen, two knife-edge(KE) models were used to predict the attenuation by a personin a frequency range from 4 to 10GHz in [32]. In addition toregarding a human body as an absorbing screen, a cylindricalmodel by uniform theory of diffraction (UTD) was alsoapplied to predict human body attenuation. Measurementsin [33, 34] were performed at 10GHz which showed astrong correlation between a human body and a perfectconducing cylinder. Previous works about penetration lossesof material in mmWave bands were focused on 28GHzand 60GHz. In [35], signals through a hollow plasterboardwall resulted in a penetration loss ranging between 5.4 dBand 8.1 dB. In [36], the measured penetration losses are2 dB, 9 dB, and 35.5 dB at 60GHz through a glass door, aplasterboard wall withmetallic studs, and a wall with ametal-backed blackboard, respectively. For this reason, it wouldbe of interest to carry out measurements of the attenuationat 26 and 39GHz by a human body and trees as well aspenetration losses for material with a person lateral crossingthe transceiver connection line and to use KE and UTDmethods to predict its attenuation. Also it would be of interestto measure the attenuation by willow trees at 26GHz andthen to compare with ITU-R P-833-8 model and modify themodel at 26GHz. An interesting investigation would alsobe carrying out measurements of the penetration loss fordifferentmaterials as well, for example, transparent glass withdifferent thickness, frosted glass, and wood with plastic clad.

4 International Journal of Antennas and Propagation

5G wireless communication networks are expected tofulfill the demand for higher data rates, lower latency, and/ormassive connectivity of a growing number of users/devicesexploiting a variety of wireless applications. This envisionedrapid increase in the use of wireless services would lead thewireless research community to start looking at new tech-nologies to address problems related to the RF propagationmodeling. This includes the development of models for newconcepts such asmassiveMIMOsystems to improve the spec-tral efficiency at the link and network layers and developingnovel propagation models for characterizing communicationin particular in the upper mmWave.

Generally, we need to continue to progress in our researchfor appropriate 5G radio propagation models, which canadequately and faithfully model mmWave communicationproperties much more than what has been done at themoment. The progress reported in this Special Edition is justa small step in achieving this goal in the future.

Mihajlo StefanovicStefan R. Panic

Rausley A. A. de SouzaJuan Reig

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Editorial Recent Advances in RF Propagation Modeling for ...downloads.hindawi.com/journals/ijap/2017/4701208.pdf · InternationalJournalofAntennasandPropagation 3 that is, the Wireless